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  3. Bayesian Decision Analysis
  • Cited by 68
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    • Publisher:
      Cambridge University Press
      Publication date:
      June 2012
      September 2010
      ISBN:
      9780511779237
      9780521764544
      DOI:
      https://doi.org/10.1017/CBO9780511779237
      Dimensions:
      (247 x 174 mm)
      Weight & Pages:
      0.84kg, 348 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Organisation Studies, Optimization, OR and risk, Statistics and Probability, Management
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    Subjects:
    Organisation Studies, Optimization, OR and risk, Statistics and Probability, Management
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    Book description

    Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem, how data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years, all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics.

    Reviews

    ‘The author presents a good set of solved exercises, which serve for illustration, and a large set of proposed exercises are suggested. I recommend this book for professional and advanced students in statistics, operations research, computer science, artificial intelligence, cognitive sciences and different branches of engineering.’

    Narciso Bouza Herrera Source: Zentralblatt MATH

    '… an excellent resource for students at final year undergraduate level or higher, and for anyone researching issues of complex decision-making.'

    Source: Mathematics Today

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